Search results for "Server log"

showing 4 items of 4 documents

Initial experiences in radiology e-learning

2007

The use of two different educator-centric learning management systems (LMSs), Moodle and Manila, for radiology e-learning was formatively evaluated and the implications of the future use of LMSs in radiology education were explored. NeuroRAD, a neuroradiologic digital library and learning community, is implemented with Moodle, one of the most popular open-source educator-centric LMSs. Pediatric-Education.org, a pediatric digital library and learning community, is implemented with Manila, a commercial educator-centric LMS. Quantitative and qualitative analyses of these LMSs were performed with World Wide Web server log file statistical programs and user-submitted comment forms. In 2005, Neur…

Publishingmedicine.medical_specialtyInternetbusiness.industryAttitude of Health PersonnelE-learning (theory)Learning communityComputer-Assisted InstructionServer logDigital libraryUnited StatesAttitude to ComputerPublishingComputingMilieux_COMPUTERSANDEDUCATIONmedicineRadiology Nuclear Medicine and imagingThe InternetLearning ManagementEducation Medical ContinuingRadiologybusinessRadiologyComputer-Assisted Instruction
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Adaptive framework for network traffic classification using dimensionality reduction and clustering

2012

Information security has become a very important topic especially during the last years. Web services are becoming more complex and dynamic. This offers new possibilities for attackers to exploit vulnerabilities by inputting malicious queries or code. However, these attack attempts are often recorded in server logs. Analyzing these logs could be a way to detect intrusions either periodically or in real time. We propose a framework that preprocesses and analyzes these log files. HTTP queries are transformed to numerical matrices using n-gram analysis. The dimensionality of these matrices is reduced using principal component analysis and diffusion map methodology. Abnormal log lines can then …

ta113Computer scienceNetwork securitybusiness.industryDimensionality reductionintrusion detectionk-meansdiffusion mapServer logcomputer.software_genreanomaly detectionTraffic classificationkoneoppiminenWeb log analysis softwareAnomaly detectionData miningWeb servicetiedonlouhintaCluster analysisbusinesscomputern-grams
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Application of neural network to predict purchases in online store

2016

A key ability of competitive online stores is effective prediction of customers’ purchase intentions as it makes it possible to apply personalized service strategy to convert visitors into buyers and increase sales conversion rates. Data mining and artificial intelligence techniques have proven to be successful in classification and prediction tasks in complex real-time systems, like e-commerce sites. In this paper we proposed a back-propagation neural network model aiming at predicting purchases in active user sessions in a Web store. The neural network training and evaluation was performed using a set of user sessions reconstructed from server log data. The proposed neural network was abl…

Web usage miningService strategyRecallArtificial neural networkWeb miningbusiness.industryComputer scienceneural networklog file analysisE-commerceServer logMachine learningcomputer.software_genreartificial intelligenceSet (abstract data type)Web miningonline storeKey (cryptography)e-commerceWeb storeArtificial intelligencebusinesscomputer
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Identifying legitimate Web users and bots with different traffic profiles — an Information Bottleneck approach

2020

Abstract Recent studies reported that about half of Web users nowadays are intelligent agents (Web bots). Many bots are impersonators operating at a very high sophistication level, trying to emulate navigational behaviors of legitimate users (humans). Moreover, bot technology continues to evolve which makes bot detection even harder. To deal with this problem, many advanced methods for differentiating bots from humans have been proposed, a large part of which relies on supervised machine learning techniques. In this paper, we propose a novel approach to identify various profiles of bots and humans which combines feature selection and unsupervised learning of HTTP-level traffic patterns to d…

Web userInformation Systems and ManagementComputer scienceInternet robotFeature selection02 engineering and technologyMachine learningcomputer.software_genreUnsupervised learningSession (web analytics)Management Information SystemsIntelligent agentArtificial Intelligence020204 information systemsMachine learning0202 electrical engineering electronic engineering information engineeringCluster analysisBot detectionbusiness.industryInformation bottleneck methodWeb botServer logHierarchical clusteringUnsupervised learning020201 artificial intelligence & image processingArtificial intelligencebusinesscomputerSoftwareKnowledge-Based Systems
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